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In this paper, we report the experimental implementation of handling the reconstruction problem from few angle data-sets for digital holographic microtomography. First, the digital holographic microscopy with sample-rotating scheme is established and few holograms with regularly spaced angle steps are recorded. Then, an algebraic iterative reconstruction algorithm with non-positivity constraint and a smoothing operator is applied to reconstruct three-dimensional refractive index distribution of the measured sample from the few angle data-sets. The experimental results demonstrate that the algebraic iterative technique can accurately reconstruct refractive index distribution from few angle data-sets in digital holographic microtomography. The technique is easy to implement and reduces greatly the required recording times. [ABSTRACT FROM AUTHOR]

Pattern formation is one of the many applications of diffractive optical elements (DOEs) for display. Since DOEs have lightweight and slim nature compared to other optical devices, using them as image projection device in virtual keyboards is suggested. In this paper, we present an approach to designing elements that produce distinct intensity patterns, in the far field, for two wavelengths. These two patterns are images of bilingual virtual keyboard. To achieve this with DOEs is not simple, as they are inherently wavelength specific. Our technique is based on phase periodic characteristic of wavefront using iterative algorithm to design the phase profiles. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the effect of anisotropic and correlated non-identical distributions of feature points’ gray level on pose estimation in stereo vision system. The generalized orthogonal iteration (GOI) algorithm for pose estimation with uncertainty-weighted measuring error of feature target is proposed. In this method, the inverse covariance matrix is applied to describe the uncertainty of feature points, and weighted contribution of uncertainty to the error objective function is analysed. By transforming the uncertainty into the covariance-weighted data space, a novel objective function based on spatial collinear error is constructed. The orthogonal iterative algorithm is extended to stereo vision system for pose estimation and the GOI algorithm is deduced, by which the optimized solution to a novel objective function is given. Finally, simulation and actual experimental results show high accuracy and strong robustness of the proposed approach, and should therefore, have potential for a variety of engineering applications. [ABSTRACT FROM PUBLISHER]